Conditional random fields (CRF) loss, aligns the predicted localization map \(\mathrm {M}\)  with the boundaries of a concerned object presented in input \(\mathrm {x}\) . CRF loss [1]} between \(\mathrm {x}\)  and \(\mathrm {M}\)  can be defined as follows:
\(\mathcal {L}_{CRF} (\mathrm {A}, \mathrm {M}) = \sum _{i=0}^{i=1} {M_{i}}^T A (1-M_{i})\) 
